Having a secure network is vital in today’s digital landscape and with so many headlines about data breaches and identity theft, security is of the utmost importance. For some companies, this loss of information to the often unknown hacker is a huge embarrassment and can lead to enormous losses in sales and widespread consumer mistrust.
Even the United States Federal Government, specifically the Postal Services branch, was listed in the biggest hacks of 2014. Fingers quickly pointed to China for the loss of more than 800,000 employee social security numbers and home addresses. Other notable names included:
Ebay, who leaked a whopping 145 million in user info.
Target had a huge breach in 2013 that spilled well into 2014 causing their CEO to resign and was said to cost the retailer over $110 million.
Sony was slapped by North Korea and some of the red faces included celebrities and even President Obama was tarnished by the deed.
Home Depot who chants, “more savings, more doing,” had more hacks with more than 109 million customers affected, and over 50 million credit card numbers and email addresses.
JP Morgan’s credit card hack was said to reach 80 million households and 7 million businesses in the US.
Spotify reported unauthorized access to a single user and recommended their Android users update with a fix after this one isolated incident. Those examples are just a handful of security slip-ups from 2014 and similar instances date back even further.
Understanding Big Data
The simple definition of big data is extremely large sets of data that are analyzed to reveal patterns, associations and trends that are computed to better understand human behavior and interactions. The concept is still somewhat overwhelming and difficult for most to digest. It’s much more than a simple financial calculation, like payments and interest on a business loan.
According to Data Science Central, big data has four layers that offer a simpler and more accurate breakdown on how it all works:
Sources: Can include sales records, customer database, feedback, social media channels, marketing list, email archives and any other relevant data.
Storage: Where the data resides after it is gathered and depending on the volume of information, larger amounts are utilized in a more sophisticated environment like Apache.
Processing: At this point, different methods are used to select the data to be analyzed and recognize trends and patterns.
Output: The data is then delivered in different formats that are more easily understood, charts, graphs, figures and recommendations.
How Does Big Data Protect Network Security?
Ironically enough, systems within the big data servers themselves, some are called Software Defined Networking (SDN) and other types of analytical strategies, are designed to provide a comprehensive overview of each and every network in the systems. These controllers allow network administrators to detect threats from more than just a single location.
Protection In Action
In this example, many hospitals are using behavior analysis software to prevent the misuse of patients’ personal information. These types of software systems can detect abnormal network behavior and identify individuals or employees who may be inappropriately accessing and leaking sensitive and confidential patient information.
Network administrators can also set pre-defined rules and parameters that ensure more secure network operations. These rules can identify and eliminate suspicious and/or unauthorized access immediately rather than finding the intruder later. These automated processes increase speed and efficiency while reducing overall IT costs. Also, these types of control systems and automations will only continue to improve with time.
More Secure Staffing
According to Monster.com, one of the largest online employment sites, more recruiters are utilizing big data for staffing and hiring. In their advice section, Monster states that the research firm Gartner predicts that the growth of big data will explode by 800% over the next five years and that 80% of this data will be “unstructured,” which includes things like resumes, emails and social media posts.
Monster states that recruiters “Will leverage the power of predictive recruitment analytics solutions and big data intelligence technology to optimize their talent pipeline and resource investments,” which will help find the most talented candidate. With additional data coming from criminal and military records, more secure candidates will rise to the surface.
As big data continues to mature and evolve, it will become a more effective and affordable solution for many endeavors, including more secure networks and a safer overall environment.
Nick Rojas is a business consultant and writer who lives in Los Angeles. He has consulted small and medium-sized enterprises for over twenty years. He has contributed articles to Visual.ly, Entrepreneur, and TechCrunch. You can follow him on Twitter @NickARojas, or you can reach him at [email protected].